The field of the invention is systems and methods for magnetic resonance imaging (“MRI”). More particularly, the invention relates to systems and methods for improved parametric mapping with MRI.
MRI uses the nuclear magnetic resonance phenomenon to produce images. When a substance, such as human tissue, is subjected to a uniform magnetic field, such as the so-called main magnetic field, B0, of an MRI system, the individual magnetic moments of the nuclei in the tissue attempt to align with this B0 field, but precess about it in random order at their characteristic Larmor frequency, ω. If the substance, or tissue, is subjected to a so-called excitation electromagnetic field, B1, that has a frequency near the Larmor frequency, the net aligned magnetic moment, referred to as longitudinal magnetization, may be rotated, or “tipped,” into the transverse plane to produce a net transverse magnetic moment, referred to as transverse magnetization. A magnetic resonance signal is emitted by the excited nuclei or “spins,” after the excitation field, B1, is terminated, and this signal may be received and processed to form an image.
Magnetic resonance parametric mapping is a general framework for measuring physically meaningful biomarkers. In general, parametric mapping includes obtaining several images from the same field-of-view using different acquisition parameters, such as echo time, repetition time, flip angle diffusion weighting gradients, motion encoding gradients, and so on. These different acquisition parameters give rise to images where the contrast varies in a controlled way. For example, in chemical-shift encoded imaging, several images are acquired with different echo times, which gives rise to different relative phases between distinct chemical species.
A map of a desired parameter is then produced from the image series. The desired parameter is typically mapped by fitting a signal model to the acquired images at each voxel. For instance, in chemical-shift encoded imaging, fat-water separation and R*2 measurements can be obtained from the acquired images.
Parametric mapping has a number of important applications in MRI, including mapping of contrast dynamics, diffusion, quantification of fat and iron, functional blood oxygen level dependent imaging, and so on. However, parametric mapping is negatively affected by the presence of image artifacts and noise. These effects can introduce systematic errors in certain areas of the parameter maps.
It would therefore be desirable to identify these areas to avoid performing measurements in locations where the measured parameter values are unreliable.